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It is useful for regression, classification, dimensionality reduction, feature learning, topic modelling and collaborative filtering. Restricted Boltzmann Machines are stochastic two layered neural networks which belong to a category of energy based models that can detect inherent patterns automatically in the data by reconstructing input.
The value of the Boltzmann constant is measured using J/K or m 2 Kgs -2 K -1. Which is mostly observed in Boltzmann’s entropy formula and Planck’s law of Black body radiation. The values of Boltzmann constant is obtained by dividing gas constant R by Avogadro’s number N A.
The Boltzmann distribution law states that the probability of finding the molecule in a particular energy state varies exponentially as the energy divided by kBT The observed speed distribution of gas molecules in thermal equilibrium is shown at right P(v) is called the Maxwell- Boltzmann speed distribution function P(v) P(v)
Boltzmann’s paradigm was an ideal gas of N identical particles, of which Ni are in the i -th microscopic condition (range) of position and momentum. For this case, the probability of each microstate of the system is equal, so it was equivalent for Boltzmann to calculate the number of microstates associated with a macrostate.